MétaCan
Menu
Back to cohort
Record W3154106394

The Evolution of Community Consultation in GTA Transit Planning

2020· article· en· W3154106394 on OpenAlexfundaboutno aff
Nick Lombardo

Bibliographic record

VenueTSpace · 2020
Typearticle
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsTransit (satellite)Environmental planningBusinessGeographyTransport engineeringPublic transportEngineering
DOInot available

Abstract

fetched live from OpenAlex

During the immediate postwar period, transit infrastructure underwent a vast expansion in the Toronto area. Tens of kilometres of new subway lines were built and commuter rail was introduced across one of the fastest-growing urban regions in Canada. This period was also characterized by a top-down approach to planning, with limited community consultation. Today, community consultation is formally embedded in the transit planning process, but is often the source of tension and mistrust. This paper describes what has changed since the 1960s. Using case studies of the Bloor-Danforth Subway (1966), the Davenport Diamond Project (2015– ), and the Hurontario Light Rail Transit Project (2010– ), the paper explores how planning in the immediate postwar period reflected a top-down, hierarchical structure that did not offer opportunities for meaningful community consultation and in which access, equity, and community-building were not priorities. In contrast, much contemporary planning has been characterized by the inability to satisfy an increased desire for public input in a meaningful way. The result is distrust between the public and planners.This paper suggests that community consultation should be integrated into the earliest stages of the planning process to ensure that such plans proceed into the expensive construction process, with its numerous contracted-out labour and technical aspects, with much broader support.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score0.308

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.025
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0260.031
Scholarly communication0.0110.006
Open science0.0020.017
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.297
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueTSpaceSame topicTransportation and Mobility InnovationsFrench-language works237,207